Bayesian inference

Individualized morphometric-similarity deviations in autism linked to cortical hierarchy and microarchitecture

The paper identifies individualized cortical deviations in autism linked to brain hierarchy and microarchitecture through morphometric similarity networks and Bayesian regression.

Evaluating genomic offset predictions in a forest tree with high population genetic structure

This study evaluates genomic offset predictions in maritime pine using multiple methods and data sources, finding strong associations with mortality but not height.

Does slow oscillation-spindle coupling contribute to sleep-dependent memory consolidation? A Bayesian meta-analysis

This paper conducts a Bayesian meta-analysis of 23 studies to assess the role of slow oscillation-spindle coupling in memory consolidation, finding strong evidence for its predictive value.

Bayesian multi-state multi-condition modeling of a protein structure based on X-ray crystallography data

The paper develops MultiXray, a Bayesian method for multi-state and multi-condition protein structure modeling using X-ray crystallography data, improving Rfree values in both simulated and experimental cases.

Structurally Informed Fitness Landscapes for Surveillance of Emerging PRRSV Variants

This paper introduces EscaPRRS, a Bayesian variational autoencoder that predicts antibody escape propensities of PRRSV GP5 mutants using structural and sequence data, showing strong correlation with binding affinities.

Genome-wide association studies identify shared mechanisms between hypertension and type 2 diabetes independent of adiposity

Estimating fruit tree growth curves in breeding field using fragmented longitudinal data: An application to citrus hybrid seedlings

The paper estimates growth curves for citrus hybrid seedlings using fragmented longitudinal data and Bayesian nonlinear models, showing improved parameter estimation with genomic integration.

Human Kidney Alternative Splicing Information Illuminates Cardiovascular-Kidney-Metabolic Syndrome Risk

The paper identifies splicing variants in human kidney tissue associated with kidney function and cardiovascular-kidney-metabolic syndrome traits using long-read RNA sequencing and QTL analysis.

A versatile data repository for GWAS summary statistics-based downstream genomic analysis of human complex traits

The paper introduces gact, an R package that integrates GWAS summary statistics with genomic resources to identify causal genes and pathways, demonstrating its application in coronary artery disease and type 2 diabetes.

Genome-wide association study of susceptibility to acute respiratory distress syndrome

This study identifies a genome-wide significant variant associated with sepsis-associated ARDS risk, linking cholesterol metabolism to ARDS susceptibility.

How many characters are needed to reconstruct a phylogeny?

This study investigates how many discrete characters are needed for accurate Bayesian phylogenetic estimation, finding that 100-500 variable characters are sufficient for 20 taxa.

Efficient Protein Engineering via Integrated Language Models and Bayesian Optimization

This study uses protein language models and Bayesian optimization to improve protein engineering efficiency by predicting function from sequences and optimizing variant search.

MACHINE: a robust and scalable multi-ancestry fine-mapping method using a continuous global-local shrinkage prior

MACHINE improves multi-ancestry fine-mapping by using a continuous prior and FDR control, identifying new causal variants in lipid traits and schizophrenia.

Estimating Disorder Probability Based on Polygenic Prediction Using the BPC Approach

The paper introduces the BPC approach to improve polygenic score calibration for binary disorders, achieving better calibration than existing methods in simulated and empirical data.

High-density genome-wide association study points out major candidate genes for resistance to infectious pancreatic necrosis in rainbow trout

This study identifies candidate genes for IPN resistance in rainbow trout using a high-density genome-wide association study and Bayesian modeling.

Mapping genetic effects on splicing in ten thousand post-mortem brain samples reveals novel mediators of neurological disease risk

The paper maps genetic effects on splicing in 10,725 brain samples, identifying 68,358 cis-sQTLs and 97 loci where splicing mediates neurological disease risk.

Fast and standardized motor-hotspot determination with automated TMS mapping

This paper develops an automated algorithm for determining motor hotspots and thresholds in TMS, achieving faster and more accurate results than previous methods.

Blood flow simulation and uncertainty quantification in extensive microvascular networks: Application to brain cortical networks

This paper develops an adaptive method for setting pressure boundary conditions in microvascular blood flow simulations and quantifies uncertainty in hemodynamic predictions across brain cortical networks.

Bayesian inference of lineage trees by joint analysis of single-cell multimodal lineage-tracing data with BiLinT

BiLinT jointly models lineage barcodes and gene expression to reconstruct high-resolution lineage trees with improved accuracy.

Inferring Personalized Cell-Cell Communication Networks in Colorectal Cancer with Individualized Causal Discovery

This paper develops a framework to infer individualized cell-cell communication networks in colorectal cancer using causal discovery methods applied to single-cell RNA-seq data.

Calibration and refinement of ACMG/AMP criteria for variant classification with BayesQuantify

BayesQuantify refines ACMG/AMP variant classification criteria using Bayesian methods, providing objective thresholds for evidence levels across multiple datasets.

Biobank-scale Bayesian TWAS reveals splicing-mediated mechanisms of complex disease

The paper uses Bayesian TWAS to identify splicing-disease associations across multiple cohorts, revealing causal mechanisms in immune, vascular, and metabolic traits.

Bridging biology and statistics with hybrid Bayesian experimental design for drug dose-response assays

This paper introduces a Bayesian framework for optimizing drug dose-response assays to improve information efficiency and reduce trial-and-error in cancer research.

Multivariate Trait Evolution: Models for the Evolution of the Quantitative Genetic G-Matrix on Phylogenies.

This paper develops analytical models for the evolution of genetic covariance matrices (G-matrices) on phylogenies, unifying quantitative genetics and macroevolutionary theory.

Bayesian causal inference unifies perceptual and neuronal processing of center-surround motion in area MT

This paper shows that Bayesian causal inference explains both perceptual and neuronal center-surround motion effects in area MT by linking motion integration and contextual response modulation.

The Genetic Relationships Between Post-Traumatic Stress Disorder and Its Corresponding Neural Circuit Structures

This study identifies genetic links between PTSD and brain circuitry traits using GWAS meta-analysis and multiple genetic methods, finding shared loci and causal relationships.

RealTrace: Uncovering biological dynamics hidden under measurement noise in time-lapse microscopy data

RealTrace is a Bayesian method that removes measurement noise from time-lapse microscopy data to reveal biological dynamics, showing fluctuating growth rates and gene expression in single cells.

Uncertainty Modeling Outperforms Machine Learning for Microbiome Data Analysis

This paper shows Bayesian partially identified models outperform machine learning and normalization methods in microbiome data analysis by accounting for uncertainty in microbial load.

Prior expectations guide multisensory integration during face-to-face communication

This study uses Bayesian computational modeling to show that prior expectations guide multisensory integration during face-to-face communication, with stronger integration when signals convey congruent communicative intent.

A Bayesian Informative Shrinkage Approach for Large-scale Multiple Hypothesis Testing (BISHOT): with Applications in Differential Analysis of Omics Data

The paper introduces a Bayesian method for differential analysis of omics data that incorporates prior knowledge across platforms or species, improving robustness and generalizability.